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The Scientific World Journal
Volume 2014 (2014), Article ID 736106, 8 pages
Research Article

Pain Expression Recognition Based on pLSA Model

Department of Information Management, Hunan University of Finance and Economics, Changsha 410205, China

Received 9 January 2014; Accepted 19 February 2014; Published 27 March 2014

Academic Editors: Y.-B. Yuan and S. Zhao

Copyright © 2014 Shaoping Zhu. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


We present a new approach to automatically recognize the pain expression from video sequences, which categorize pain as 4 levels: “no pain,” “slight pain,” “moderate pain,” and “ severe pain.” First of all, facial velocity information, which is used to characterize pain, is determined using optical flow technique. Then visual words based on facial velocity are used to represent pain expression using bag of words. Final pLSA model is used for pain expression recognition, in order to improve the recognition accuracy, the class label information was used for the learning of the pLSA model. Experiments were performed on a pain expression dataset built by ourselves to test and evaluate the proposed method, the experiment results show that the average recognition accuracy is over 92%, which validates its effectiveness.